Overview

Dataset statistics

Number of variables36
Number of observations92218
Missing cells294960
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.0 MiB
Average record size in memory296.0 B

Variable types

Categorical9
Numeric21
DateTime5
Text1

Alerts

ThrowHand has constant value ""Constant
ASLRCoreStabilityLeft has constant value ""Constant
PitchId is highly overall correlated with HipChestSeparationPeak and 1 other fieldsHigh correlation
Velocity is highly overall correlated with HorizontalBreak and 1 other fieldsHigh correlation
HorizontalBreak is highly overall correlated with Velocity and 1 other fieldsHigh correlation
InducedVerticalBreak is highly overall correlated with Velocity and 1 other fieldsHigh correlation
KneeStrideFlexionFC is highly overall correlated with HipExternalRotatationPassiveLeft and 2 other fieldsHigh correlation
KneeStrideFlexionAngVeloPeak is highly overall correlated with HipChestSeparationPeak and 3 other fieldsHigh correlation
ShoulderThrowRotationMER is highly overall correlated with HipExternalRotatationPassiveLeft and 3 other fieldsHigh correlation
ElbowThrowFlexionFC is highly overall correlated with RightAvgBrakingForceNewtons and 3 other fieldsHigh correlation
HipChestSeparationPeak is highly overall correlated with PitchId and 2 other fieldsHigh correlation
GripLeft is highly overall correlated with GripRight and 7 other fieldsHigh correlation
GripRight is highly overall correlated with GripLeft and 5 other fieldsHigh correlation
HipExternalRotatationPassiveLeft is highly overall correlated with KneeStrideFlexionFC and 7 other fieldsHigh correlation
HipExternalRotatationPassiveRight is highly overall correlated with ShoulderThrowRotationMER and 10 other fieldsHigh correlation
ShoulderExternalRotatationStrengthLeft is highly overall correlated with ShoulderThrowRotationMER and 10 other fieldsHigh correlation
ShoulderExternalRotatationStrengthRight is highly overall correlated with ShoulderThrowRotationMER and 9 other fieldsHigh correlation
AvgBrakingForceNewtons is highly overall correlated with PeakPropulsiveForceNewtons and 6 other fieldsHigh correlation
PeakPropulsiveForceNewtons is highly overall correlated with KneeStrideFlexionFC and 5 other fieldsHigh correlation
LeftAvgBrakingForceNewtons is highly overall correlated with KneeStrideFlexionFC and 9 other fieldsHigh correlation
RightAvgBrakingForceNewtons is highly overall correlated with ElbowThrowFlexionFC and 6 other fieldsHigh correlation
PlayerCode is highly overall correlated with ElbowThrowFlexionFC and 13 other fieldsHigh correlation
PitchType is highly overall correlated with InducedVerticalBreakHigh correlation
BodyPart is highly overall correlated with KneeStrideFlexionAngVeloPeak and 13 other fieldsHigh correlation
BodySide is highly overall correlated with PitchId and 13 other fieldsHigh correlation
Diagnosis is highly overall correlated with ElbowThrowFlexionFC and 11 other fieldsHigh correlation
CombinedDiagnosis is highly overall correlated with ElbowThrowFlexionFC and 11 other fieldsHigh correlation
ASLRCoreStabilityRight is highly overall correlated with HorizontalBreak and 12 other fieldsHigh correlation
GripLeft has 1152 (1.2%) missing valuesMissing
GripRight has 1152 (1.2%) missing valuesMissing
HipExternalRotatationPassiveLeft has 30553 (33.1%) missing valuesMissing
HipExternalRotatationPassiveRight has 30553 (33.1%) missing valuesMissing
ShoulderExternalRotatationStrengthLeft has 30553 (33.1%) missing valuesMissing
ShoulderExternalRotatationStrengthRight has 30553 (33.1%) missing valuesMissing
ASLRCoreStabilityLeft has 41260 (44.7%) missing valuesMissing
ASLRCoreStabilityRight has 41260 (44.7%) missing valuesMissing
AvgBrakingForceNewtons has 17654 (19.1%) missing valuesMissing
PeakPropulsiveForceNewtons has 8654 (9.4%) missing valuesMissing
JumpHeightMeters has 8654 (9.4%) missing valuesMissing
ImpulseRatio has 17654 (19.1%) missing valuesMissing
LeftAvgBrakingForceNewtons has 17654 (19.1%) missing valuesMissing
RightAvgBrakingForceNewtons has 17654 (19.1%) missing valuesMissing

Reproduction

Analysis started2023-11-15 00:38:35.549046
Analysis finished2023-11-15 00:39:20.229348
Duration44.68 seconds
Software versionydata-profiling vv4.6.0
Download configurationconfig.json

Variables

PlayerCode
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
VX9I
23712 
KYOF
23000 
VR1T
7920 
MR7S
7808 
LI18
6600 
Other values (6)
23178 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters368872
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVR1T
2nd rowVR1T
3rd rowVR1T
4th rowVR1T
5th rowVR1T

Common Values

ValueCountFrequency (%)
VX9I 23712
25.7%
KYOF 23000
24.9%
VR1T 7920
 
8.6%
MR7S 7808
 
8.5%
LI18 6600
 
7.2%
L8DC 6360
 
6.9%
2D7B 5760
 
6.2%
63FZ 3696
 
4.0%
L6I5 3444
 
3.7%
YXS2 2178
 
2.4%

Length

2023-11-14T16:39:20.286705image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
vx9i 23712
25.7%
kyof 23000
24.9%
vr1t 7920
 
8.6%
mr7s 7808
 
8.5%
li18 6600
 
7.2%
l8dc 6360
 
6.9%
2d7b 5760
 
6.2%
63fz 3696
 
4.0%
l6i5 3444
 
3.7%
yxs2 2178
 
2.4%

Most occurring characters

ValueCountFrequency (%)
I 33756
 
9.2%
V 33372
 
9.0%
X 27630
 
7.5%
F 26696
 
7.2%
Y 25178
 
6.8%
9 23712
 
6.4%
K 23000
 
6.2%
O 23000
 
6.2%
L 18144
 
4.9%
R 15728
 
4.3%
Other values (15) 118656
32.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 281894
76.4%
Decimal Number 86978
 
23.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 33756
12.0%
V 33372
11.8%
X 27630
9.8%
F 26696
9.5%
Y 25178
8.9%
K 23000
8.2%
O 23000
8.2%
L 18144
6.4%
R 15728
 
5.6%
D 12120
 
4.3%
Other values (7) 43270
15.3%
Decimal Number
ValueCountFrequency (%)
9 23712
27.3%
1 14520
16.7%
7 13568
15.6%
8 12960
14.9%
2 7938
 
9.1%
6 7140
 
8.2%
3 3696
 
4.2%
5 3444
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 281894
76.4%
Common 86978
 
23.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 33756
12.0%
V 33372
11.8%
X 27630
9.8%
F 26696
9.5%
Y 25178
8.9%
K 23000
8.2%
O 23000
8.2%
L 18144
6.4%
R 15728
 
5.6%
D 12120
 
4.3%
Other values (7) 43270
15.3%
Common
ValueCountFrequency (%)
9 23712
27.3%
1 14520
16.7%
7 13568
15.6%
8 12960
14.9%
2 7938
 
9.1%
6 7140
 
8.2%
3 3696
 
4.2%
5 3444
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 368872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 33756
 
9.2%
V 33372
 
9.0%
X 27630
 
7.5%
F 26696
 
7.2%
Y 25178
 
6.8%
9 23712
 
6.4%
K 23000
 
6.2%
O 23000
 
6.2%
L 18144
 
4.9%
R 15728
 
4.3%
Other values (15) 118656
32.2%

PitchId
Real number (ℝ)

HIGH CORRELATION 

Distinct456
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.473704
Minimum1
Maximum456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:20.738119image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q118
median46
Q3100
95-th percentile368
Maximum456
Range455
Interquartile range (IQR)82

Descriptive statistics

Standard deviation109.4217
Coefficient of variation (CV)1.2367708
Kurtosis2.4048059
Mean88.473704
Median Absolute Deviation (MAD)33
Skewness1.8356395
Sum8158868
Variance11973.108
MonotonicityNot monotonic
2023-11-14T16:39:20.818102image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1324
 
1.4%
1 1324
 
1.4%
15 1324
 
1.4%
14 1324
 
1.4%
13 1324
 
1.4%
12 1324
 
1.4%
11 1324
 
1.4%
8 1324
 
1.4%
4 1324
 
1.4%
3 1324
 
1.4%
Other values (446) 78978
85.6%
ValueCountFrequency (%)
1 1324
1.4%
2 1324
1.4%
3 1324
1.4%
4 1324
1.4%
5 1324
1.4%
6 1324
1.4%
7 1324
1.4%
8 1324
1.4%
9 1324
1.4%
10 1324
1.4%
ValueCountFrequency (%)
456 52
0.1%
455 52
0.1%
454 52
0.1%
453 52
0.1%
452 52
0.1%
451 52
0.1%
450 52
0.1%
449 52
0.1%
448 52
0.1%
447 52
0.1%
Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2023-03-14 00:00:00
Maximum2023-07-29 00:00:00
2023-11-14T16:39:20.889212image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:20.957651image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
Distinct1042
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:21.158384image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters829962
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 23:25:11
2nd row 23:25:11
3rd row 23:25:11
4th row 23:25:11
5th row 23:25:11
ValueCountFrequency (%)
19:17:06 382
 
0.4%
19:01:03 330
 
0.4%
19:01:41 330
 
0.4%
19:15:56 330
 
0.4%
19:02:44 330
 
0.4%
19:03:01 330
 
0.4%
19:14:38 330
 
0.4%
19:14:53 330
 
0.4%
19:16:25 330
 
0.4%
19:00:49 330
 
0.4%
Other values (1032) 88866
96.4%
2023-11-14T16:39:21.429306image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 184436
22.2%
1 119402
14.4%
0 117668
14.2%
92218
11.1%
2 73202
 
8.8%
4 52328
 
6.3%
3 44018
 
5.3%
5 41762
 
5.0%
7 33012
 
4.0%
9 25964
 
3.1%
Other values (2) 45952
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 553308
66.7%
Other Punctuation 184436
 
22.2%
Space Separator 92218
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 119402
21.6%
0 117668
21.3%
2 73202
13.2%
4 52328
9.5%
3 44018
 
8.0%
5 41762
 
7.5%
7 33012
 
6.0%
9 25964
 
4.7%
6 25926
 
4.7%
8 20026
 
3.6%
Other Punctuation
ValueCountFrequency (%)
: 184436
100.0%
Space Separator
ValueCountFrequency (%)
92218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 829962
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 184436
22.2%
1 119402
14.4%
0 117668
14.2%
92218
11.1%
2 73202
 
8.8%
4 52328
 
6.3%
3 44018
 
5.3%
5 41762
 
5.0%
7 33012
 
4.0%
9 25964
 
3.1%
Other values (2) 45952
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 829962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 184436
22.2%
1 119402
14.4%
0 117668
14.2%
92218
11.1%
2 73202
 
8.8%
4 52328
 
6.3%
3 44018
 
5.3%
5 41762
 
5.0%
7 33012
 
4.0%
9 25964
 
3.1%
Other values (2) 45952
 
5.5%

ThrowHand
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
R
92218 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters92218
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowR
2nd rowR
3rd rowR
4th rowR
5th rowR

Common Values

ValueCountFrequency (%)
R 92218
100.0%

Length

2023-11-14T16:39:21.514710image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:21.580013image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
r 92218
100.0%

Most occurring characters

ValueCountFrequency (%)
R 92218
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 92218
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 92218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 92218
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 92218
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92218
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 92218
100.0%

PitchType
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
FB
44268 
SL
24822 
CH
12152 
CB
 
3944
CT
 
3264
Other values (2)
 
3768

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters184436
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCB
2nd rowCB
3rd rowCB
4th rowCB
5th rowCB

Common Values

ValueCountFrequency (%)
FB 44268
48.0%
SL 24822
26.9%
CH 12152
 
13.2%
CB 3944
 
4.3%
CT 3264
 
3.5%
SP 2488
 
2.7%
SI 1280
 
1.4%

Length

2023-11-14T16:39:21.626039image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:21.690644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
fb 44268
48.0%
sl 24822
26.9%
ch 12152
 
13.2%
cb 3944
 
4.3%
ct 3264
 
3.5%
sp 2488
 
2.7%
si 1280
 
1.4%

Most occurring characters

ValueCountFrequency (%)
B 48212
26.1%
F 44268
24.0%
S 28590
15.5%
L 24822
13.5%
C 19360
10.5%
H 12152
 
6.6%
T 3264
 
1.8%
P 2488
 
1.3%
I 1280
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 184436
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 48212
26.1%
F 44268
24.0%
S 28590
15.5%
L 24822
13.5%
C 19360
10.5%
H 12152
 
6.6%
T 3264
 
1.8%
P 2488
 
1.3%
I 1280
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 184436
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 48212
26.1%
F 44268
24.0%
S 28590
15.5%
L 24822
13.5%
C 19360
10.5%
H 12152
 
6.6%
T 3264
 
1.8%
P 2488
 
1.3%
I 1280
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 184436
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 48212
26.1%
F 44268
24.0%
S 28590
15.5%
L 24822
13.5%
C 19360
10.5%
H 12152
 
6.6%
T 3264
 
1.8%
P 2488
 
1.3%
I 1280
 
0.7%

Velocity
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.328022
Minimum72.978328
Maximum99.148787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:21.765115image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum72.978328
5-th percentile78.367018
Q183.471159
median88.894881
Q393.545214
95-th percentile96.249122
Maximum99.148787
Range26.170458
Interquartile range (IQR)10.074055

Descriptive statistics

Standard deviation5.895073
Coefficient of variation (CV)0.066740689
Kurtosis-1.0290651
Mean88.328022
Median Absolute Deviation (MAD)4.9300201
Skewness-0.33576703
Sum8145433.5
Variance34.751886
MonotonicityNot monotonic
2023-11-14T16:39:21.849632image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88.33348237 330
 
0.4%
94.39910801 330
 
0.4%
83.36131369 330
 
0.4%
78.91203183 330
 
0.4%
78.09569221 330
 
0.4%
79.10388061 330
 
0.4%
80.64740763 330
 
0.4%
94.98734402 330
 
0.4%
93.38015731 330
 
0.4%
94.67286616 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
72.97832819 52
 
0.1%
73.3756951 132
0.1%
73.73102889 66
0.1%
73.93801915 52
 
0.1%
74.23026138 132
0.1%
74.27116216 42
 
< 0.1%
74.3649345 42
 
< 0.1%
74.48682358 42
 
< 0.1%
74.5325875 42
 
< 0.1%
74.56593757 42
 
< 0.1%
ValueCountFrequency (%)
99.14878666 200
0.2%
98.71237515 200
0.2%
97.95939793 200
0.2%
97.89205439 200
0.2%
97.83524004 200
0.2%
97.66319837 200
0.2%
97.5339045 200
0.2%
97.42026504 200
0.2%
97.37319954 200
0.2%
97.07269187 200
0.2%

HorizontalBreak
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.7548592
Minimum-18.794367
Maximum21.133459
Zeros0
Zeros (%)0.0%
Negative61724
Negative (%)66.9%
Memory size1.4 MiB
2023-11-14T16:39:21.933741image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-18.794367
5-th percentile-14.475232
Q1-10.74023
median-7.2411094
Q34.2056676
95-th percentile14.911366
Maximum21.133459
Range39.927827
Interquartile range (IQR)14.945898

Descriptive statistics

Standard deviation9.3189624
Coefficient of variation (CV)-2.4818407
Kurtosis-0.47999028
Mean-3.7548592
Median Absolute Deviation (MAD)5.1571915
Skewness0.78720226
Sum-346265.61
Variance86.84306
MonotonicityNot monotonic
2023-11-14T16:39:22.016971image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.896056285 330
 
0.4%
-10.74023031 330
 
0.4%
-13.61554148 330
 
0.4%
15.28428694 330
 
0.4%
18.8324387 330
 
0.4%
20.15313754 330
 
0.4%
17.30282201 330
 
0.4%
-8.502931871 330
 
0.4%
-10.35187193 330
 
0.4%
-5.57453235 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
-18.79436746 52
0.1%
-18.60369175 52
0.1%
-17.98819157 52
0.1%
-17.63232952 90
0.1%
-17.17232107 64
0.1%
-17.15739465 64
0.1%
-17.05320478 90
0.1%
-16.9571936 52
0.1%
-16.95418047 52
0.1%
-16.92990206 64
0.1%
ValueCountFrequency (%)
21.13345949 64
 
0.1%
21.06025677 64
 
0.1%
20.15313754 330
0.4%
20.00475852 64
 
0.1%
19.91527574 52
 
0.1%
19.53541234 52
 
0.1%
19.42360209 52
 
0.1%
19.28394065 52
 
0.1%
19.21520819 52
 
0.1%
19.21129625 64
 
0.1%

InducedVerticalBreak
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9362566
Minimum-17.67044
Maximum22.084603
Zeros0
Zeros (%)0.0%
Negative10600
Negative (%)11.5%
Memory size1.4 MiB
2023-11-14T16:39:22.103658image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-17.67044
5-th percentile-3.189247
Q12.7801263
median10.72898
Q315.696132
95-th percentile18.469749
Maximum22.084603
Range39.755042
Interquartile range (IQR)12.916006

Descriptive statistics

Standard deviation7.7436382
Coefficient of variation (CV)0.86654162
Kurtosis-0.36118107
Mean8.9362566
Median Absolute Deviation (MAD)6.1380688
Skewness-0.56883715
Sum824083.71
Variance59.963933
MonotonicityNot monotonic
2023-11-14T16:39:22.184345image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.891417633 330
 
0.4%
16.98476642 330
 
0.4%
1.7591018 330
 
0.4%
0.74178395 330
 
0.4%
1.876018994 330
 
0.4%
-0.135276658 330
 
0.4%
0.215815711 330
 
0.4%
17.96016004 330
 
0.4%
15.61197169 330
 
0.4%
17.43519644 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
-17.67043959 42
< 0.1%
-17.64386483 42
< 0.1%
-16.85797141 42
< 0.1%
-16.63686142 42
< 0.1%
-16.61134993 42
< 0.1%
-16.30499014 42
< 0.1%
-16.1124281 42
< 0.1%
-16.07494605 42
< 0.1%
-15.82414246 42
< 0.1%
-15.5481647 42
< 0.1%
ValueCountFrequency (%)
22.08460289 42
 
< 0.1%
21.84897302 42
 
< 0.1%
21.7632121 42
 
< 0.1%
21.39881682 42
 
< 0.1%
21.34508792 42
 
< 0.1%
21.26452317 42
 
< 0.1%
21.15786485 42
 
< 0.1%
21.10395722 42
 
< 0.1%
21.01519069 42
 
< 0.1%
21.0040342 132
0.1%

KneeStrideFlexionFC
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.934271
Minimum9.3091801
Maximum75.692113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:22.268942image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum9.3091801
5-th percentile36.843871
Q142.368931
median47.389523
Q352.313838
95-th percentile68.315792
Maximum75.692113
Range66.382933
Interquartile range (IQR)9.9449069

Descriptive statistics

Standard deviation8.9981483
Coefficient of variation (CV)0.18771847
Kurtosis2.9508019
Mean47.934271
Median Absolute Deviation (MAD)4.9837894
Skewness0.12147977
Sum4420402.6
Variance80.966673
MonotonicityNot monotonic
2023-11-14T16:39:22.348866image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43.60107566 330
 
0.4%
42.12542514 330
 
0.4%
37.91895928 330
 
0.4%
41.18841586 330
 
0.4%
42.76237021 330
 
0.4%
45.36839465 330
 
0.4%
41.93306839 330
 
0.4%
43.96500983 330
 
0.4%
43.45838889 330
 
0.4%
42.86583298 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
9.309180128 112
0.1%
10.38673586 112
0.1%
10.52318989 112
0.1%
10.95683395 112
0.1%
11.03512562 112
0.1%
12.49366776 112
0.1%
12.97232718 112
0.1%
15.36911733 132
0.1%
16.11687343 112
0.1%
22.84040203 112
0.1%
ValueCountFrequency (%)
75.69211275 120
0.1%
73.91496583 120
0.1%
73.30660204 120
0.1%
73.11067277 120
0.1%
72.92910601 120
0.1%
72.5716523 120
0.1%
72.28075618 120
0.1%
72.26505173 120
0.1%
72.0189729 120
0.1%
71.78930669 120
0.1%

KneeStrideFlexionAngVeloPeak
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean325.33463
Minimum57.464634
Maximum570.29009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:22.431607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum57.464634
5-th percentile110.1286
Q1176.43844
median367.79368
Q3437.17303
95-th percentile489.51647
Maximum570.29009
Range512.82545
Interquartile range (IQR)260.7346

Descriptive statistics

Standard deviation133.77982
Coefficient of variation (CV)0.41120683
Kurtosis-1.2736019
Mean325.33463
Median Absolute Deviation (MAD)91.352041
Skewness-0.44426549
Sum30001709
Variance17897.04
MonotonicityNot monotonic
2023-11-14T16:39:22.511936image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
425.3177926 330
 
0.4%
423.3040349 330
 
0.4%
310.4663411 330
 
0.4%
376.3827404 330
 
0.4%
407.0948055 330
 
0.4%
381.8398385 330
 
0.4%
429.202192 330
 
0.4%
431.2571062 330
 
0.4%
405.9550023 330
 
0.4%
389.2532385 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
57.46463413 52
0.1%
57.89458193 52
0.1%
61.96915867 52
0.1%
63.31332326 52
0.1%
64.44129464 52
0.1%
68.38760054 52
0.1%
69.95677683 52
0.1%
73.09595299 52
0.1%
74.12890952 52
0.1%
74.58146618 52
0.1%
ValueCountFrequency (%)
570.290089 112
0.1%
525.5223302 64
0.1%
523.4546323 64
0.1%
523.4480069 64
0.1%
521.1360946 64
0.1%
513.1754925 132
0.1%
512.4414222 64
0.1%
511.9269119 64
0.1%
511.1688117 64
0.1%
510.8026404 132
0.1%

ShoulderThrowRotationMER
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-186.84015
Minimum-539.81899
Maximum-169.21188
Zeros0
Zeros (%)0.0%
Negative92218
Negative (%)100.0%
Memory size1.4 MiB
2023-11-14T16:39:22.592428image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-539.81899
5-th percentile-197.85158
Q1-193.35266
median-185.88471
Q3-179.11116
95-th percentile-174.13363
Maximum-169.21188
Range370.60711
Interquartile range (IQR)14.241498

Descriptive statistics

Standard deviation18.301834
Coefficient of variation (CV)-0.097954502
Kurtosis297.16783
Mean-186.84015
Median Absolute Deviation (MAD)7.0377914
Skewness-15.530078
Sum-17230025
Variance334.95714
MonotonicityNot monotonic
2023-11-14T16:39:22.674193image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200.0959805 330
 
0.4%
-196.4578262 330
 
0.4%
-200.4134829 330
 
0.4%
-197.584508 330
 
0.4%
-196.4787711 330
 
0.4%
-195.4320256 330
 
0.4%
-196.2680955 330
 
0.4%
-195.7943127 330
 
0.4%
-196.5827911 330
 
0.4%
-196.6482332 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
-539.8189892 200
0.2%
-200.5612007 330
0.4%
-200.4134829 330
0.4%
-200.0959805 330
0.4%
-200.0909387 120
 
0.1%
-199.9868919 120
 
0.1%
-199.9797987 330
0.4%
-199.8705626 120
 
0.1%
-199.8157283 112
 
0.1%
-199.7577872 112
 
0.1%
ValueCountFrequency (%)
-169.2118784 200
0.2%
-169.4658233 200
0.2%
-169.4987856 200
0.2%
-169.5282257 200
0.2%
-169.6090537 200
0.2%
-169.8593487 200
0.2%
-169.8717347 200
0.2%
-170.5268925 200
0.2%
-170.6708417 200
0.2%
-171.3102729 200
0.2%

ElbowThrowFlexionFC
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.20254
Minimum36.280024
Maximum132.87466
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:22.760702image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum36.280024
5-th percentile75.962344
Q199.834176
median104.40303
Q3111.07722
95-th percentile123.27669
Maximum132.87466
Range96.59464
Interquartile range (IQR)11.243041

Descriptive statistics

Standard deviation13.231405
Coefficient of variation (CV)0.12697777
Kurtosis4.0680331
Mean104.20254
Median Absolute Deviation (MAD)5.6598009
Skewness-1.2981396
Sum9609349.6
Variance175.07009
MonotonicityNot monotonic
2023-11-14T16:39:22.840436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.2013749 330
 
0.4%
126.5273887 330
 
0.4%
115.4467846 330
 
0.4%
121.2067144 330
 
0.4%
120.7001136 330
 
0.4%
118.8954222 330
 
0.4%
119.8885413 330
 
0.4%
122.5455023 330
 
0.4%
122.9857598 330
 
0.4%
123.6093102 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
36.28002445 112
0.1%
39.81479444 112
0.1%
40.90524042 112
0.1%
41.49560719 112
0.1%
44.17032651 112
0.1%
46.37422484 112
0.1%
46.71587275 112
0.1%
47.45992523 112
0.1%
62.27660524 132
0.1%
69.00489528 132
0.1%
ValueCountFrequency (%)
132.8746644 66
 
0.1%
132.4201888 66
 
0.1%
132.1252499 66
 
0.1%
130.7809855 66
 
0.1%
130.2428992 66
 
0.1%
130.1222961 66
 
0.1%
129.3875599 66
 
0.1%
128.5953864 66
 
0.1%
128.4581793 330
0.4%
128.4553463 66
 
0.1%

HipChestSeparationPeak
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.535221
Minimum37.206183
Maximum75.69585
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:22.924148image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum37.206183
5-th percentile44.488465
Q148.374635
median51.879645
Q356.195402
95-th percentile71.085872
Maximum75.69585
Range38.489668
Interquartile range (IQR)7.8207666

Descriptive statistics

Standard deviation7.6380318
Coefficient of variation (CV)0.14267302
Kurtosis0.89454485
Mean53.535221
Median Absolute Deviation (MAD)3.8240192
Skewness1.126241
Sum4936911.1
Variance58.33953
MonotonicityNot monotonic
2023-11-14T16:39:23.008174image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.2613651 330
 
0.4%
69.09167027 330
 
0.4%
67.18938992 330
 
0.4%
71.04304357 330
 
0.4%
69.84085946 330
 
0.4%
73.62531791 330
 
0.4%
70.12677511 330
 
0.4%
67.37024002 330
 
0.4%
66.72778598 330
 
0.4%
70.80499783 330
 
0.4%
Other values (1043) 88918
96.4%
ValueCountFrequency (%)
37.20618266 42
 
< 0.1%
37.51502486 52
 
0.1%
37.53300215 66
0.1%
37.64517252 42
 
< 0.1%
37.66812798 42
 
< 0.1%
37.92720995 132
0.1%
38.14216163 42
 
< 0.1%
38.25444343 42
 
< 0.1%
39.27494879 66
0.1%
39.40267051 42
 
< 0.1%
ValueCountFrequency (%)
75.69585031 330
0.4%
75.26196662 112
 
0.1%
75.2613651 330
0.4%
74.44280813 112
 
0.1%
74.39353871 112
 
0.1%
74.33224635 112
 
0.1%
73.62531791 330
0.4%
73.53731837 112
 
0.1%
73.36384562 112
 
0.1%
73.27537999 112
 
0.1%
Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2023-03-17 00:00:00
Maximum2023-08-08 00:00:00
2023-11-14T16:39:23.078537image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:23.141502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

BodyPart
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Arm/Elbow
46736 
Pelvis/Hips
23712 
Shoulder
19592 
Head
 
2178

Length

Max length11
Median length9
Mean length9.1837168
Min length4

Characters and Unicode

Total characters846904
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowArm/Elbow
2nd rowArm/Elbow
3rd rowArm/Elbow
4th rowArm/Elbow
5th rowArm/Elbow

Common Values

ValueCountFrequency (%)
Arm/Elbow 46736
50.7%
Pelvis/Hips 23712
25.7%
Shoulder 19592
21.2%
Head 2178
 
2.4%

Length

2023-11-14T16:39:23.212852image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:23.283166image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
arm/elbow 46736
50.7%
pelvis/hips 23712
25.7%
shoulder 19592
21.2%
head 2178
 
2.4%

Most occurring characters

ValueCountFrequency (%)
l 90040
 
10.6%
/ 70448
 
8.3%
o 66328
 
7.8%
r 66328
 
7.8%
i 47424
 
5.6%
s 47424
 
5.6%
A 46736
 
5.5%
m 46736
 
5.5%
E 46736
 
5.5%
b 46736
 
5.5%
Other values (11) 271968
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 613790
72.5%
Uppercase Letter 162666
 
19.2%
Other Punctuation 70448
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 90040
14.7%
o 66328
10.8%
r 66328
10.8%
i 47424
7.7%
s 47424
7.7%
m 46736
7.6%
b 46736
7.6%
w 46736
7.6%
e 45482
7.4%
v 23712
 
3.9%
Other values (5) 86844
14.1%
Uppercase Letter
ValueCountFrequency (%)
A 46736
28.7%
E 46736
28.7%
H 25890
15.9%
P 23712
14.6%
S 19592
12.0%
Other Punctuation
ValueCountFrequency (%)
/ 70448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 776456
91.7%
Common 70448
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 90040
 
11.6%
o 66328
 
8.5%
r 66328
 
8.5%
i 47424
 
6.1%
s 47424
 
6.1%
A 46736
 
6.0%
m 46736
 
6.0%
E 46736
 
6.0%
b 46736
 
6.0%
w 46736
 
6.0%
Other values (10) 225232
29.0%
Common
ValueCountFrequency (%)
/ 70448
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 846904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 90040
 
10.6%
/ 70448
 
8.3%
o 66328
 
7.8%
r 66328
 
7.8%
i 47424
 
5.6%
s 47424
 
5.6%
A 46736
 
5.5%
m 46736
 
5.5%
E 46736
 
5.5%
b 46736
 
5.5%
Other values (11) 271968
32.1%

BodySide
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
R
66328 
L
23712 
O
 
2178

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters92218
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowR
2nd rowR
3rd rowR
4th rowR
5th rowR

Common Values

ValueCountFrequency (%)
R 66328
71.9%
L 23712
 
25.7%
O 2178
 
2.4%

Length

2023-11-14T16:39:23.340654image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:23.398483image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
r 66328
71.9%
l 23712
 
25.7%
o 2178
 
2.4%

Most occurring characters

ValueCountFrequency (%)
R 66328
71.9%
L 23712
 
25.7%
O 2178
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 92218
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 66328
71.9%
L 23712
 
25.7%
O 2178
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 92218
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 66328
71.9%
L 23712
 
25.7%
O 2178
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92218
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 66328
71.9%
L 23712
 
25.7%
O 2178
 
2.4%

Diagnosis
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Strain
64268 
Tendinitis
14520 
Impingement Syndrome
11252 
Concussion
 
2178

Length

Max length20
Median length6
Mean length8.4324969
Min length6

Characters and Unicode

Total characters777628
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTendinitis
2nd rowTendinitis
3rd rowTendinitis
4th rowTendinitis
5th rowTendinitis

Common Values

ValueCountFrequency (%)
Strain 64268
69.7%
Tendinitis 14520
 
15.7%
Impingement Syndrome 11252
 
12.2%
Concussion 2178
 
2.4%

Length

2023-11-14T16:39:23.453769image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:23.518988image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
strain 64268
62.1%
tendinitis 14520
 
14.0%
impingement 11252
 
10.9%
syndrome 11252
 
10.9%
concussion 2178
 
2.1%

Most occurring characters

ValueCountFrequency (%)
n 131420
16.9%
i 121258
15.6%
t 90040
11.6%
S 75520
9.7%
r 75520
9.7%
a 64268
8.3%
e 48276
 
6.2%
m 33756
 
4.3%
d 25772
 
3.3%
s 18876
 
2.4%
Other values (10) 92922
11.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 662906
85.2%
Uppercase Letter 103470
 
13.3%
Space Separator 11252
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 131420
19.8%
i 121258
18.3%
t 90040
13.6%
r 75520
11.4%
a 64268
9.7%
e 48276
 
7.3%
m 33756
 
5.1%
d 25772
 
3.9%
s 18876
 
2.8%
o 15608
 
2.4%
Other values (5) 38112
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
S 75520
73.0%
T 14520
 
14.0%
I 11252
 
10.9%
C 2178
 
2.1%
Space Separator
ValueCountFrequency (%)
11252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 766376
98.6%
Common 11252
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 131420
17.1%
i 121258
15.8%
t 90040
11.7%
S 75520
9.9%
r 75520
9.9%
a 64268
8.4%
e 48276
 
6.3%
m 33756
 
4.4%
d 25772
 
3.4%
s 18876
 
2.5%
Other values (9) 81670
10.7%
Common
ValueCountFrequency (%)
11252
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 777628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 131420
16.9%
i 121258
15.6%
t 90040
11.6%
S 75520
9.7%
r 75520
9.7%
a 64268
8.3%
e 48276
 
6.2%
m 33756
 
4.3%
d 25772
 
3.3%
s 18876
 
2.4%
Other values (10) 92922
11.9%

CombinedDiagnosis
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
R Arm/Elbow Strain
38816 
L Pelvis/Hips Strain
23712 
R Shoulder Impingement Syndrome
11252 
R Arm/Elbow Tendinitis
7920 
R Shoulder Tendinitis
6600 
Other values (2)
3918 

Length

Max length31
Median length22
Mean length20.616214
Min length17

Characters and Unicode

Total characters1901186
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowR Arm/Elbow Tendinitis
2nd rowR Arm/Elbow Tendinitis
3rd rowR Arm/Elbow Tendinitis
4th rowR Arm/Elbow Tendinitis
5th rowR Arm/Elbow Tendinitis

Common Values

ValueCountFrequency (%)
R Arm/Elbow Strain 38816
42.1%
L Pelvis/Hips Strain 23712
25.7%
R Shoulder Impingement Syndrome 11252
 
12.2%
R Arm/Elbow Tendinitis 7920
 
8.6%
R Shoulder Tendinitis 6600
 
7.2%
O Head Concussion 2178
 
2.4%
R Shoulder Strain 1740
 
1.9%

Length

2023-11-14T16:39:23.581574image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:23.652762image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
r 66328
23.0%
strain 64268
22.3%
arm/elbow 46736
16.2%
l 23712
 
8.2%
pelvis/hips 23712
 
8.2%
shoulder 19592
 
6.8%
tendinitis 14520
 
5.0%
impingement 11252
 
3.9%
syndrome 11252
 
3.9%
o 2178
 
0.8%
Other values (2) 4356
 
1.5%

Most occurring characters

ValueCountFrequency (%)
195688
 
10.3%
i 168682
 
8.9%
r 141848
 
7.5%
n 131420
 
6.9%
S 95112
 
5.0%
e 93758
 
4.9%
l 90040
 
4.7%
t 90040
 
4.7%
o 81936
 
4.3%
m 80492
 
4.2%
Other values (23) 732170
38.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1276696
67.2%
Uppercase Letter 358354
 
18.8%
Space Separator 195688
 
10.3%
Other Punctuation 70448
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 168682
13.2%
r 141848
11.1%
n 131420
10.3%
e 93758
 
7.3%
l 90040
 
7.1%
t 90040
 
7.1%
o 81936
 
6.4%
m 80492
 
6.3%
a 66446
 
5.2%
s 66300
 
5.2%
Other values (10) 265734
20.8%
Uppercase Letter
ValueCountFrequency (%)
S 95112
26.5%
R 66328
18.5%
E 46736
13.0%
A 46736
13.0%
H 25890
 
7.2%
L 23712
 
6.6%
P 23712
 
6.6%
T 14520
 
4.1%
I 11252
 
3.1%
O 2178
 
0.6%
Space Separator
ValueCountFrequency (%)
195688
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 70448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1635050
86.0%
Common 266136
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 168682
 
10.3%
r 141848
 
8.7%
n 131420
 
8.0%
S 95112
 
5.8%
e 93758
 
5.7%
l 90040
 
5.5%
t 90040
 
5.5%
o 81936
 
5.0%
m 80492
 
4.9%
a 66446
 
4.1%
Other values (21) 595276
36.4%
Common
ValueCountFrequency (%)
195688
73.5%
/ 70448
 
26.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1901186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
195688
 
10.3%
i 168682
 
8.9%
r 141848
 
7.5%
n 131420
 
6.9%
S 95112
 
5.0%
e 93758
 
4.9%
l 90040
 
4.7%
t 90040
 
4.7%
o 81936
 
4.3%
m 80492
 
4.2%
Other values (23) 732170
38.5%

GripLeft
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct43
Distinct (%)< 0.1%
Missing1152
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean159.85046
Minimum95.700798
Maximum197.96468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:23.735698image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum95.700798
5-th percentile114.88732
Q1145.75553
median157.50921
Q3180.74197
95-th percentile197.96468
Maximum197.96468
Range102.26388
Interquartile range (IQR)34.986439

Descriptive statistics

Standard deviation23.126094
Coefficient of variation (CV)0.1446733
Kurtosis-0.057842932
Mean159.85046
Median Absolute Deviation (MAD)17.152042
Skewness-0.37991689
Sum14556942
Variance534.8162
MonotonicityNot monotonic
2023-11-14T16:39:23.813417image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
167.4976716 5928
 
6.4%
156.1285345 5928
 
6.4%
174.7898983 5928
 
6.4%
165.5584764 5928
 
6.4%
180.7419731 4600
 
5.0%
184.0925037 4600
 
5.0%
190.6122798 4600
 
5.0%
191.9997559 4600
 
5.0%
197.9646832 4600
 
5.0%
157.5092133 2640
 
2.9%
Other values (33) 41714
45.2%
ValueCountFrequency (%)
95.70079824 1152
1.2%
97.07402499 1152
1.2%
114.8795876 1152
1.2%
114.8873204 1148
1.2%
121.6486851 1152
1.2%
126.0001272 1148
1.2%
129.7333877 1148
1.2%
134.845475 1590
1.7%
135.0678817 1590
1.7%
135.6663451 1590
1.7%
ValueCountFrequency (%)
197.9646832 4600
5.0%
191.9997559 4600
5.0%
190.6122798 4600
5.0%
184.0925037 4600
5.0%
180.7419731 4600
5.0%
174.7898983 5928
6.4%
167.4976716 5928
6.4%
166.1207282 1320
 
1.4%
165.5584764 5928
6.4%
161.9097208 1320
 
1.4%

GripRight
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct43
Distinct (%)< 0.1%
Missing1152
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean163.58348
Minimum99.640817
Maximum193.41114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:23.890120image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum99.640817
5-th percentile111.89982
Q1148.22592
median171.58622
Q3180.34178
95-th percentile193.41114
Maximum193.41114
Range93.770322
Interquartile range (IQR)32.115862

Descriptive statistics

Standard deviation21.876901
Coefficient of variation (CV)0.13373539
Kurtosis0.056675594
Mean163.58348
Median Absolute Deviation (MAD)17.106955
Skewness-0.79476982
Sum14896894
Variance478.59879
MonotonicityNot monotonic
2023-11-14T16:39:23.966432image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
188.6931707 5928
 
6.4%
174.5382103 5928
 
6.4%
181.2299584 5928
 
6.4%
178.3647818 5928
 
6.4%
193.4111396 4600
 
5.0%
179.6923543 4600
 
5.0%
182.0643014 4600
 
5.0%
171.586216 4600
 
5.0%
180.3417831 4600
 
5.0%
179.8750722 2640
 
2.9%
Other values (33) 41714
45.2%
ValueCountFrequency (%)
99.64081708 1152
1.2%
106.6759325 1152
1.2%
110.3645614 1152
1.2%
111.8998226 1152
1.2%
132.7092867 1320
1.4%
133.0087555 924
1.0%
133.6933091 1148
1.2%
137.5115609 1148
1.2%
137.7262298 1320
1.4%
138.5682719 924
1.0%
ValueCountFrequency (%)
193.4111396 4600
5.0%
188.6931707 5928
6.4%
182.0643014 4600
5.0%
181.2299584 5928
6.4%
180.3417831 4600
5.0%
179.8750722 2640
2.9%
179.6923543 4600
5.0%
178.3647818 5928
6.4%
174.5382103 5928
6.4%
171.586216 4600
5.0%
Distinct39
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2023-02-18 00:00:00
Maximum2023-08-07 00:00:00
2023-11-14T16:39:24.040006image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:24.112845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2023-02-22 00:00:00
Maximum2023-07-22 00:00:00
2023-11-14T16:39:24.185824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:24.252624image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

HipExternalRotatationPassiveLeft
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)< 0.1%
Missing30553
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean33.445715
Minimum19.211221
Maximum48.57563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:24.317384image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum19.211221
5-th percentile26.742781
Q126.926464
median32.149454
Q339.401758
95-th percentile48.57563
Maximum48.57563
Range29.364409
Interquartile range (IQR)12.475294

Descriptive statistics

Standard deviation7.3443918
Coefficient of variation (CV)0.21959141
Kurtosis-0.63579414
Mean33.445715
Median Absolute Deviation (MAD)5.2229903
Skewness0.57471715
Sum2062430
Variance53.940091
MonotonicityNot monotonic
2023-11-14T16:39:24.377724image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
26.7427814 11500
 
12.5%
29.74493396 11500
 
12.5%
26.92646412 5760
 
6.2%
44.473823 3960
 
4.3%
32.23186006 3960
 
4.3%
39.40175838 3904
 
4.2%
48.57562966 3300
 
3.6%
45.40592121 3300
 
3.6%
32.14945443 3180
 
3.4%
35.26808674 3180
 
3.4%
Other values (5) 8121
 
8.8%
(Missing) 30553
33.1%
ValueCountFrequency (%)
19.21122051 1740
 
1.9%
26.7427814 11500
12.5%
26.92646412 5760
6.2%
29.74493396 11500
12.5%
32.14945443 3180
 
3.4%
32.23186006 3960
 
4.3%
35.26808674 3180
 
3.4%
35.70598711 1722
 
1.9%
36.00556801 1089
 
1.2%
36.50320689 1722
 
1.9%
ValueCountFrequency (%)
48.57562966 3300
3.6%
45.40592121 3300
3.6%
44.473823 3960
4.3%
42.55258653 1848
2.0%
39.40175838 3904
4.2%
36.50320689 1722
1.9%
36.00556801 1089
 
1.2%
35.70598711 1722
1.9%
35.26808674 3180
3.4%
32.23186006 3960
4.3%

HipExternalRotatationPassiveRight
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)< 0.1%
Missing30553
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean31.990661
Minimum21.950532
Maximum46.939179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:24.439966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum21.950532
5-th percentile21.950532
Q123.749192
median31.75677
Q338.480554
95-th percentile46.939179
Maximum46.939179
Range24.988647
Interquartile range (IQR)14.731363

Descriptive statistics

Standard deviation8.4387504
Coefficient of variation (CV)0.26378793
Kurtosis-1.3051365
Mean31.990661
Median Absolute Deviation (MAD)8.0075784
Skewness0.26585291
Sum1972704.1
Variance71.212508
MonotonicityNot monotonic
2023-11-14T16:39:24.501259image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
21.95053186 11500
 
12.5%
23.74919151 11500
 
12.5%
30.27928267 5760
 
6.2%
46.93917875 3960
 
4.3%
35.90838406 3960
 
4.3%
44.04357448 3904
 
4.2%
42.96689249 3300
 
3.6%
35.08814944 3300
 
3.6%
31.75676995 3180
 
3.4%
38.4805544 3180
 
3.4%
Other values (5) 8121
 
8.8%
(Missing) 30553
33.1%
ValueCountFrequency (%)
21.95053186 11500
12.5%
23.74919151 11500
12.5%
26.63816969 1740
 
1.9%
30.27928267 5760
6.2%
31.75676995 3180
 
3.4%
35.08814944 3300
 
3.6%
35.90838406 3960
 
4.3%
36.05033378 1722
 
1.9%
36.69870284 1089
 
1.2%
37.917355 1722
 
1.9%
ValueCountFrequency (%)
46.93917875 3960
4.3%
44.04357448 3904
4.2%
42.96689249 3300
3.6%
42.26307659 1848
2.0%
38.4805544 3180
3.4%
37.917355 1722
1.9%
36.69870284 1089
 
1.2%
36.05033378 1722
1.9%
35.90838406 3960
4.3%
35.08814944 3300
3.6%

ShoulderExternalRotatationStrengthLeft
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)< 0.1%
Missing30553
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean58.656398
Minimum33.863814
Maximum82.831239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:24.561450image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum33.863814
5-th percentile35.15412
Q146.724666
median53.686716
Q371.16179
95-th percentile82.831239
Maximum82.831239
Range48.967425
Interquartile range (IQR)24.437123

Descriptive statistics

Standard deviation15.591404
Coefficient of variation (CV)0.2658091
Kurtosis-1.1975347
Mean58.656398
Median Absolute Deviation (MAD)10.755792
Skewness0.29193196
Sum3617046.8
Variance243.09189
MonotonicityNot monotonic
2023-11-14T16:39:24.622013image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
82.83123896 11500
 
12.5%
71.1617895 11500
 
12.5%
46.72466645 5760
 
6.2%
49.37743008 3960
 
4.3%
35.15412021 3960
 
4.3%
55.93501429 3904
 
4.2%
42.93092378 3300
 
3.6%
52.61526093 3300
 
3.6%
47.38317059 3180
 
3.4%
46.23423641 3180
 
3.4%
Other values (5) 8121
 
8.8%
(Missing) 30553
33.1%
ValueCountFrequency (%)
33.86381432 1740
 
1.9%
35.15412021 3960
4.3%
42.93092378 3300
3.6%
46.23423641 3180
3.4%
46.72466645 5760
6.2%
47.38317059 3180
3.4%
49.37743008 3960
4.3%
49.39494812 1722
 
1.9%
52.61526093 3300
3.6%
53.68671612 1722
 
1.9%
ValueCountFrequency (%)
82.83123896 11500
12.5%
71.1617895 11500
12.5%
59.79638267 1848
 
2.0%
58.71304702 1089
 
1.2%
55.93501429 3904
 
4.2%
53.68671612 1722
 
1.9%
52.61526093 3300
 
3.6%
49.39494812 1722
 
1.9%
49.37743008 3960
 
4.3%
47.38317059 3180
 
3.4%

ShoulderExternalRotatationStrengthRight
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)< 0.1%
Missing30553
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean56.361374
Minimum28.234395
Maximum78.099105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:24.681929image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum28.234395
5-th percentile38.519851
Q141.453039
median51.030889
Q370.561127
95-th percentile78.099105
Maximum78.099105
Range49.86471
Interquartile range (IQR)29.108088

Descriptive statistics

Standard deviation15.644163
Coefficient of variation (CV)0.27756888
Kurtosis-1.5285584
Mean56.361374
Median Absolute Deviation (MAD)12.511038
Skewness0.13481094
Sum3475524.1
Variance244.73985
MonotonicityNot monotonic
2023-11-14T16:39:24.746584image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
70.56112681 11500
 
12.5%
78.09910515 11500
 
12.5%
39.90689977 5760
 
6.2%
48.42637889 3960
 
4.3%
44.25702842 3960
 
4.3%
65.55987267 3904
 
4.2%
38.51985082 3300
 
3.6%
41.45303925 3300
 
3.6%
44.33276079 3180
 
3.4%
43.98969826 3180
 
3.4%
Other values (5) 8121
 
8.8%
(Missing) 30553
33.1%
ValueCountFrequency (%)
28.23439517 1740
 
1.9%
38.51985082 3300
3.6%
39.90689977 5760
6.2%
40.12007384 1722
 
1.9%
41.45303925 3300
3.6%
43.98969826 3180
3.4%
44.25702842 3960
4.3%
44.33276079 3180
3.4%
48.42637889 3960
4.3%
51.0308892 1089
 
1.2%
ValueCountFrequency (%)
78.09910515 11500
12.5%
70.56112681 11500
12.5%
65.55987267 3904
 
4.2%
56.43154134 1848
 
2.0%
52.40824807 1722
 
1.9%
51.0308892 1089
 
1.2%
48.42637889 3960
 
4.3%
44.33276079 3180
 
3.4%
44.25702842 3960
 
4.3%
43.98969826 3180
 
3.4%

ASLRCoreStabilityLeft
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing41260
Missing (%)44.7%
Memory size1.4 MiB
1.0
50958 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters152874
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 50958
55.3%
(Missing) 41260
44.7%

Length

2023-11-14T16:39:24.811464image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:24.870424image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 50958
100.0%

Most occurring characters

ValueCountFrequency (%)
1 50958
33.3%
. 50958
33.3%
0 50958
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101916
66.7%
Other Punctuation 50958
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 50958
50.0%
0 50958
50.0%
Other Punctuation
ValueCountFrequency (%)
. 50958
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152874
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 50958
33.3%
. 50958
33.3%
0 50958
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 50958
33.3%
. 50958
33.3%
0 50958
33.3%

ASLRCoreStabilityRight
Categorical

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing41260
Missing (%)44.7%
Memory size1.4 MiB
1.0
39458 
0.0
11500 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters152874
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 39458
42.8%
0.0 11500
 
12.5%
(Missing) 41260
44.7%

Length

2023-11-14T16:39:24.920110image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-14T16:39:24.981391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 39458
77.4%
0.0 11500
 
22.6%

Most occurring characters

ValueCountFrequency (%)
0 62458
40.9%
. 50958
33.3%
1 39458
25.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101916
66.7%
Other Punctuation 50958
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62458
61.3%
1 39458
38.7%
Other Punctuation
ValueCountFrequency (%)
. 50958
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152874
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62458
40.9%
. 50958
33.3%
1 39458
25.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62458
40.9%
. 50958
33.3%
1 39458
25.8%

AvgBrakingForceNewtons
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct130
Distinct (%)0.2%
Missing17654
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean1859.3293
Minimum1246.3573
Maximum2524.9609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:25.046605image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1246.3573
5-th percentile1549.934
Q11663.7417
median1805.4483
Q32046.0752
95-th percentile2298.4395
Maximum2524.9609
Range1278.6036
Interquartile range (IQR)382.33343

Descriptive statistics

Standard deviation242.49123
Coefficient of variation (CV)0.13041866
Kurtosis-0.27596567
Mean1859.3293
Median Absolute Deviation (MAD)164.9916
Skewness0.31034856
Sum1.3863903 × 108
Variance58801.995
MonotonicityNot monotonic
2023-11-14T16:39:25.133330image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1640.456664 1824
 
2.0%
1663.741749 1824
 
2.0%
1669.076167 1824
 
2.0%
1815.102011 1824
 
2.0%
1885.076167 1824
 
2.0%
1764.552974 1824
 
2.0%
1780.447816 1824
 
2.0%
1640.079493 1824
 
2.0%
1671.552974 1824
 
2.0%
1653.759261 1824
 
2.0%
Other values (120) 56324
61.1%
(Missing) 17654
 
19.1%
ValueCountFrequency (%)
1246.357288 360
0.4%
1317.530468 360
0.4%
1338.577029 360
0.4%
1364.405849 360
0.4%
1391.366168 360
0.4%
1411.366168 360
0.4%
1424.70888 360
0.4%
1439.404515 360
0.4%
1455.192678 60
 
0.1%
1499.653995 360
0.4%
ValueCountFrequency (%)
2524.960878 424
0.5%
2486.070448 198
0.2%
2439.732529 198
0.2%
2427.313362 424
0.5%
2396.919535 424
0.5%
2374.919535 424
0.5%
2372.3988 198
0.2%
2354.666825 198
0.2%
2322.86701 198
0.2%
2315.686846 424
0.5%

PeakPropulsiveForceNewtons
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct172
Distinct (%)0.2%
Missing8654
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean2495.7617
Minimum1778.3916
Maximum3309.4362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:25.217953image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1778.3916
5-th percentile2069.1009
Q12174.1926
median2581.6806
Q32799.8992
95-th percentile2958.1873
Maximum3309.4362
Range1531.0446
Interquartile range (IQR)625.7066

Descriptive statistics

Standard deviation330.62493
Coefficient of variation (CV)0.13247456
Kurtosis-1.4365199
Mean2495.7617
Median Absolute Deviation (MAD)322.05425
Skewness0.067527568
Sum2.0855583 × 108
Variance109312.84
MonotonicityNot monotonic
2023-11-14T16:39:25.300731image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2299.192627 1824
 
2.0%
2361.022443 1824
 
2.0%
2249.439683 1824
 
2.0%
2125.022443 1824
 
2.0%
2140.739837 1824
 
2.0%
2082.717415 1824
 
2.0%
2156.011268 1824
 
2.0%
2267.66125 1824
 
2.0%
2180.195524 1824
 
2.0%
2174.192627 1824
 
2.0%
Other values (162) 65324
70.8%
(Missing) 8654
 
9.4%
ValueCountFrequency (%)
1778.391603 200
0.2%
1803.944216 60
 
0.1%
1815.699281 60
 
0.1%
1885.699281 60
 
0.1%
1924.920541 60
 
0.1%
1938.61135 60
 
0.1%
1960.510835 60
 
0.1%
1965.510835 60
 
0.1%
1968.61135 60
 
0.1%
1973.76255 60
 
0.1%
ValueCountFrequency (%)
3309.436203 198
0.2%
3163.98619 424
0.5%
3156.16993 198
0.2%
3107.886434 424
0.5%
3024.643833 264
0.3%
3022.088376 198
0.2%
3019.584483 320
0.3%
3012.642092 424
0.5%
2996.281702 198
0.2%
2991.742426 264
0.3%

JumpHeightMeters
Real number (ℝ)

MISSING 

Distinct165
Distinct (%)0.2%
Missing8654
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean0.44367343
Minimum-0.57388443
Maximum1.5018376
Zeros0
Zeros (%)0.0%
Negative21110
Negative (%)22.9%
Memory size1.4 MiB
2023-11-14T16:39:25.388494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-0.57388443
5-th percentile-0.43504709
Q1-0.011190428
median0.50864976
Q30.96172098
95-th percentile1.3088699
Maximum1.5018376
Range2.075722
Interquartile range (IQR)0.97291141

Descriptive statistics

Standard deviation0.55239114
Coefficient of variation (CV)1.2450399
Kurtosis-1.1632391
Mean0.44367343
Median Absolute Deviation (MAD)0.48620012
Skewness-0.085013221
Sum37075.126
Variance0.30513597
MonotonicityNot monotonic
2023-11-14T16:39:25.467516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1929044486 1824
 
2.0%
0.631775951 1824
 
2.0%
0.4040791309 1824
 
2.0%
0.8002679371 1824
 
2.0%
0.5134214582 1824
 
2.0%
0.1507048728 1824
 
2.0%
0.5434214594 1824
 
2.0%
0.2129044295 1824
 
2.0%
-0.06254967861 1824
 
2.0%
0.6517759617 1824
 
2.0%
Other values (155) 65324
70.8%
(Missing) 8654
 
9.4%
ValueCountFrequency (%)
-0.5738844294 200
 
0.2%
-0.5698055667 200
 
0.2%
-0.5561567373 60
 
0.1%
-0.5481249657 976
1.1%
-0.5381249753 976
1.1%
-0.4978102548 200
 
0.2%
-0.4961567647 60
 
0.1%
-0.4960672287 424
0.5%
-0.4898055834 200
 
0.2%
-0.4638844151 200
 
0.2%
ValueCountFrequency (%)
1.501837559 264
 
0.3%
1.423734469 60
 
0.1%
1.388749295 60
 
0.1%
1.383734477 60
 
0.1%
1.361000929 720
0.8%
1.359161709 424
0.5%
1.350455693 424
0.5%
1.341000918 360
0.4%
1.338749283 60
 
0.1%
1.329161708 424
0.5%

ImpulseRatio
Real number (ℝ)

MISSING 

Distinct130
Distinct (%)0.2%
Missing17654
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean1.7815401
Minimum0.61265509
Maximum3.6775035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:25.547514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.61265509
5-th percentile0.9316929
Q11.203943
median1.6885433
Q32.2921179
95-th percentile2.8442827
Maximum3.6775035
Range3.0648484
Interquartile range (IQR)1.0881749

Descriptive statistics

Standard deviation0.65580595
Coefficient of variation (CV)0.3681118
Kurtosis-0.7526211
Mean1.7815401
Median Absolute Deviation (MAD)0.50514137
Skewness0.35929075
Sum132838.76
Variance0.43008144
MonotonicityNot monotonic
2023-11-14T16:39:25.627729image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.527702759 1824
 
2.0%
1.041263978 1824
 
2.0%
0.9538432034 1824
 
2.0%
1.582007141 1824
 
2.0%
0.9438432129 1824
 
2.0%
1.78079376 1824
 
2.0%
1.184780143 1824
 
2.0%
1.119939064 1824
 
2.0%
1.830793712 1824
 
2.0%
1.203942987 1824
 
2.0%
Other values (120) 56324
61.1%
(Missing) 17654
 
19.1%
ValueCountFrequency (%)
0.6126550897 976
1.1%
0.662655042 976
1.1%
0.7714899569 492
 
0.5%
0.8414898901 492
 
0.5%
0.8914899617 492
 
0.5%
0.9316929043 976
1.1%
0.9400415127 60
 
0.1%
0.9438432129 1824
2.0%
0.9538432034 1824
2.0%
0.9866809426 424
 
0.5%
ValueCountFrequency (%)
3.677503527 320
 
0.3%
3.206979909 320
 
0.3%
3.178126989 320
 
0.3%
3.099058322 1150
1.2%
3.072815571 320
 
0.3%
3.070849588 360
 
0.4%
2.988979304 200
 
0.2%
2.984684072 264
 
0.3%
2.961350359 60
 
0.1%
2.957687494 60
 
0.1%

LeftAvgBrakingForceNewtons
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct130
Distinct (%)0.2%
Missing17654
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean939.70744
Minimum535.62593
Maximum1202.2957
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:25.713850image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum535.62593
5-th percentile711.08929
Q1833.75095
median938.03309
Q31048.715
95-th percentile1161.3306
Maximum1202.2957
Range666.66978
Interquartile range (IQR)214.96407

Descriptive statistics

Standard deviation136.70439
Coefficient of variation (CV)0.14547548
Kurtosis-0.1319939
Mean939.70744
Median Absolute Deviation (MAD)105.70563
Skewness-0.24408155
Sum70068346
Variance18688.09
MonotonicityNot monotonic
2023-11-14T16:39:25.796577image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
818.6026324 1824
 
2.0%
850.4880791 1824
 
2.0%
847.9508109 1824
 
2.0%
907.2959226 1824
 
2.0%
935.9508109 1824
 
2.0%
908.4307434 1824
 
2.0%
871.8521483 1824
 
2.0%
809.1263571 1824
 
2.0%
869.4307434 1824
 
2.0%
833.7509513 1824
 
2.0%
Other values (120) 56324
61.1%
(Missing) 17654
 
19.1%
ValueCountFrequency (%)
535.6259336 360
0.4%
553.1333435 360
0.4%
583.4204213 360
0.4%
590.5360542 360
0.4%
624.889411 360
0.4%
638.889411 360
0.4%
639.6772698 360
0.4%
655.8162739 360
0.4%
672.7242023 360
0.4%
704.4690554 360
0.4%
ValueCountFrequency (%)
1202.295713 424
 
0.5%
1190.134116 1150
1.2%
1180.591517 424
 
0.5%
1179.294828 424
 
0.5%
1163.202141 1150
1.2%
1161.330612 264
 
0.3%
1158.212109 1150
1.2%
1151.095628 1150
1.2%
1139.061592 424
 
0.5%
1137.684776 198
 
0.2%

RightAvgBrakingForceNewtons
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct130
Distinct (%)0.2%
Missing17654
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean919.5034
Minimum711.05219
Maximum1407.8718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2023-11-14T16:39:25.884135image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum711.05219
5-th percentile757.43518
Q1814.42438
median872.8184
Q31000.5931
95-th percentile1216.1234
Maximum1407.8718
Range696.81957
Interquartile range (IQR)186.16869

Descriptive statistics

Standard deviation140.13608
Coefficient of variation (CV)0.15240409
Kurtosis0.39514356
Mean919.5034
Median Absolute Deviation (MAD)66.024921
Skewness1.1076394
Sum68561851
Variance19638.12
MonotonicityNot monotonic
2023-11-14T16:39:25.966837image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
821.2747721 1824
 
2.0%
813.6131599 1824
 
2.0%
820.0484415 1824
 
2.0%
907.6872131 1824
 
2.0%
948.0484415 1824
 
2.0%
855.0107081 1824
 
2.0%
907.6786651 1824
 
2.0%
832.5010521 1824
 
2.0%
802.0107081 1824
 
2.0%
819.0144422 1824
 
2.0%
Other values (120) 56324
61.1%
(Missing) 17654
 
19.1%
ValueCountFrequency (%)
711.0521942 360
 
0.4%
743.28652 60
 
0.1%
748.8159726 360
 
0.4%
750.4657009 1150
1.2%
757.1235508 60
 
0.1%
757.4351811 1824
2.0%
765.1618007 360
 
0.4%
767.0523347 360
 
0.4%
773.0523347 360
 
0.4%
779.8696772 360
 
0.4%
ValueCountFrequency (%)
1407.871766 198
0.2%
1322.285989 424
0.5%
1316.153946 198
0.2%
1311.881799 424
0.5%
1284.911644 198
0.2%
1278.949021 198
0.2%
1275.036721 198
0.2%
1246.75584 424
0.5%
1235.881799 424
0.5%
1224.401689 424
0.5%
Distinct95
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2023-02-15 00:00:00
Maximum2023-07-31 00:00:00
2023-11-14T16:39:26.049956image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:26.129859image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-11-14T16:39:16.857119image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:41.077723image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:42.854361image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:44.720825image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:46.604055image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:48.560730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:50.403106image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:52.288433image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:54.098876image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:55.780594image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:57.747326image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:59.493997image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:01.180676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:02.869588image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:04.721665image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:06.360851image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:08.038130image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:09.763346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:11.760836image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:13.428797image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:15.120173image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:16.935895image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:41.162673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:42.929404image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:44.806975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:46.736064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:48.640928image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:50.481352image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:52.370802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:54.176816image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:55.867187image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:57.824159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:38:59.568335image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:01.259885image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
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2023-11-14T16:38:59.404258image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:01.101171image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:02.782743image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:04.640075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:06.277937image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:07.952514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:09.672405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:11.672688image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:13.342771image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:15.034426image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-11-14T16:39:16.768998image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2023-11-14T16:39:26.232982image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
PitchIdVelocityHorizontalBreakInducedVerticalBreakKneeStrideFlexionFCKneeStrideFlexionAngVeloPeakShoulderThrowRotationMERElbowThrowFlexionFCHipChestSeparationPeakGripLeftGripRightHipExternalRotatationPassiveLeftHipExternalRotatationPassiveRightShoulderExternalRotatationStrengthLeftShoulderExternalRotatationStrengthRightAvgBrakingForceNewtonsPeakPropulsiveForceNewtonsJumpHeightMetersImpulseRatioLeftAvgBrakingForceNewtonsRightAvgBrakingForceNewtonsPlayerCodePitchTypeBodyPartBodySideDiagnosisCombinedDiagnosisASLRCoreStabilityRight
PitchId1.000-0.107-0.036-0.133-0.256-0.3510.016-0.179-0.5490.2990.460-0.302-0.3060.4240.475-0.290-0.219-0.066-0.270-0.227-0.2890.3190.1510.4740.5790.2570.3590.388
Velocity-0.1071.000-0.5600.8230.2560.247-0.0480.1330.2830.013-0.013-0.116-0.090-0.030-0.017-0.0220.0220.0270.0840.011-0.0460.2480.4900.2610.2680.2080.2440.457
HorizontalBreak-0.036-0.5601.000-0.4450.0750.1620.1400.0630.0700.1070.0380.093-0.0300.1280.1640.1670.063-0.0160.0530.2050.0830.2640.4660.2900.2780.2200.2530.515
InducedVerticalBreak-0.1330.823-0.4451.0000.1760.1110.0400.1190.1770.0670.050-0.155-0.115-0.018-0.007-0.035-0.0130.0190.0820.003-0.0710.2610.5520.2410.2590.2210.2360.385
KneeStrideFlexionFC-0.2560.2560.0750.1761.0000.3910.4250.2690.231-0.017-0.061-0.509-0.3960.1520.1970.4820.5770.1320.2640.5380.2930.4800.1960.4210.4530.2800.3650.496
KneeStrideFlexionAngVeloPeak-0.3510.2470.1620.1110.3911.0000.287-0.0290.503-0.030-0.2400.1960.1270.1500.3300.3560.2120.0760.2170.3640.2400.4550.2290.5640.6840.3600.4880.703
ShoulderThrowRotationMER0.016-0.0480.1400.0400.4250.2871.000-0.286-0.1770.3630.221-0.709-0.7040.6590.6560.2150.4020.1650.2630.381-0.0510.0800.0480.0460.0290.0300.0540.081
ElbowThrowFlexionFC-0.1790.1330.0630.1190.269-0.029-0.2861.0000.156-0.214-0.2390.2850.168-0.135-0.2790.4300.157-0.102-0.1870.2210.5390.5100.2470.4580.3970.5500.5290.193
HipChestSeparationPeak-0.5490.2830.0700.1770.2310.503-0.1770.1561.000-0.220-0.4270.3460.269-0.376-0.4340.2090.1600.0350.2900.2060.1870.4660.2050.4720.5020.3520.4680.396
GripLeft0.2990.0130.1070.067-0.017-0.0300.363-0.214-0.2201.0000.774-0.381-0.6360.7030.710-0.192-0.129-0.1130.1380.119-0.4490.6300.2420.5580.5740.4550.4981.000
GripRight0.460-0.0130.0380.050-0.061-0.2400.221-0.239-0.4270.7741.000-0.478-0.6120.6350.745-0.243-0.166-0.090-0.0280.000-0.4320.5690.2130.5060.4720.4870.4100.348
HipExternalRotatationPassiveLeft-0.302-0.1160.093-0.155-0.5090.196-0.7090.2850.346-0.381-0.4781.0000.876-0.449-0.3490.114-0.354-0.086-0.308-0.2720.4020.8260.2900.6410.3540.7450.7821.000
HipExternalRotatationPassiveRight-0.306-0.090-0.030-0.115-0.3960.127-0.7040.1680.269-0.636-0.6120.8761.000-0.663-0.5370.094-0.3140.004-0.323-0.3710.4260.8360.2570.5790.3030.6080.6971.000
ShoulderExternalRotatationStrengthLeft0.424-0.0300.128-0.0180.1520.1500.659-0.135-0.3760.7030.635-0.449-0.6631.0000.8440.1800.341-0.0410.0670.490-0.1620.8020.3030.7280.5990.8070.7371.000
ShoulderExternalRotatationStrengthRight0.475-0.0170.164-0.0070.1970.3300.656-0.279-0.4340.7100.745-0.349-0.5370.8441.0000.1940.262-0.0230.0220.494-0.1800.8720.3000.6120.3820.6070.7181.000
AvgBrakingForceNewtons-0.290-0.0220.167-0.0350.4820.3560.2150.4300.209-0.192-0.2430.1140.0940.1800.1941.0000.8260.057-0.0430.8930.8590.5180.1810.4910.5440.5710.5470.463
PeakPropulsiveForceNewtons-0.2190.0220.063-0.0130.5770.2120.4020.1570.160-0.129-0.166-0.354-0.3140.3410.2620.8261.0000.1470.2210.8270.6370.4440.1640.4840.5380.4280.4860.538
JumpHeightMeters-0.0660.027-0.0160.0190.1320.0760.165-0.1020.035-0.113-0.090-0.0860.004-0.041-0.0230.0570.1471.000-0.0050.0700.0260.3360.1460.4200.4710.3050.3250.312
ImpulseRatio-0.2700.0840.0530.0820.2640.2170.263-0.1870.2900.138-0.028-0.308-0.3230.0670.022-0.0430.221-0.0051.0000.098-0.2000.3540.1680.4930.4830.3680.3840.494
LeftAvgBrakingForceNewtons-0.2270.0110.2050.0030.5380.3640.3810.2210.2060.1190.000-0.272-0.3710.4900.4940.8930.8270.0700.0981.0000.5760.5070.1790.5050.5540.5310.5750.725
RightAvgBrakingForceNewtons-0.289-0.0460.083-0.0710.2930.240-0.0510.5390.187-0.449-0.4320.4020.426-0.162-0.1800.8590.6370.026-0.2000.5761.0000.4460.2020.5050.5160.5650.4490.246
PlayerCode0.3190.2480.2640.2610.4800.4550.0800.5100.4660.6300.5690.8260.8360.8020.8720.5180.4440.3360.3540.5070.4461.0000.3721.0001.0001.0001.0001.000
PitchType0.1510.4900.4660.5520.1960.2290.0480.2470.2050.2420.2130.2900.2570.3030.3000.1810.1640.1460.1680.1790.2020.3721.0000.3640.2640.3750.3200.468
BodyPart0.4740.2610.2900.2410.4210.5640.0460.4580.4720.5580.5060.6410.5790.7280.6120.4910.4840.4200.4930.5050.5051.0000.3641.0001.0000.7511.0000.754
BodySide0.5790.2680.2780.2590.4530.6840.0290.3970.5020.5740.4720.3540.3030.5990.3820.5440.5380.4710.4830.5540.5161.0000.2641.0001.0000.7561.0000.549
Diagnosis0.2570.2080.2200.2210.2800.3600.0300.5500.3520.4550.4870.7450.6080.8070.6070.5710.4280.3050.3680.5310.5651.0000.3750.7510.7561.0001.0000.266
CombinedDiagnosis0.3590.2440.2530.2360.3650.4880.0540.5290.4680.4980.4100.7820.6970.7370.7180.5470.4860.3250.3840.5750.4491.0000.3201.0001.0001.0001.0000.754
ASLRCoreStabilityRight0.3880.4570.5150.3850.4960.7030.0810.1930.3961.0000.3481.0001.0001.0001.0000.4630.5380.3120.4940.7250.2461.0000.4680.7540.5490.2660.7541.000

Missing values

2023-11-14T16:39:18.727707image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-11-14T16:39:19.373083image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-11-14T16:39:19.986941image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

PlayerCodePitchIdPitchDatePitchTimeThrowHandPitchTypeVelocityHorizontalBreakInducedVerticalBreakKneeStrideFlexionFCKneeStrideFlexionAngVeloPeakShoulderThrowRotationMERElbowThrowFlexionFCHipChestSeparationPeakInjuredDateBodyPartBodySideDiagnosisCombinedDiagnosisGripLeftGripRightGripDateAssessedPerformanceDateAssessedHipExternalRotatationPassiveLeftHipExternalRotatationPassiveRightShoulderExternalRotatationStrengthLeftShoulderExternalRotatationStrengthRightASLRCoreStabilityLeftASLRCoreStabilityRightAvgBrakingForceNewtonsPeakPropulsiveForceNewtonsJumpHeightMetersImpulseRatioLeftAvgBrakingForceNewtonsRightAvgBrakingForceNewtonsJumpDateAssessed
0VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaNNaN2159.4853531.361001NaNNaNNaN2023-03-25
1VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaNNaN2142.2862751.085226NaNNaNNaN2023-04-02
2VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaN1439.4045152117.1224031.0589901.817174655.816274784.0511922023-03-23
3VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaNNaN2148.2862751.075226NaNNaNNaN2023-04-02
4VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaN1499.6539952045.246208-0.2990021.934612672.724202825.6935742023-03-16
5VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaNNaN2203.5606230.829442NaNNaNNaN2023-04-06
6VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaN1364.4058492089.3387520.9884752.282544583.420421779.8696772023-04-07
7VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaN1317.5304682101.5570821.0222902.125044553.133343765.1618012023-04-01
9VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaN1411.3661682052.378833-0.4100462.483085638.889411773.0523352023-03-26
10VR1T212023-04-0823:25:11RCB75.26355610.061752-8.95616142.692695425.256171-186.76716670.56571245.8969552023-04-08Arm/ElbowRTendinitisR Arm/Elbow Tendinitis149.962333152.6840552023-03-192023-02-2444.47382346.93917949.3774348.426379NaNNaNNaN2194.1733390.886754NaNNaNNaN2023-04-08
PlayerCodePitchIdPitchDatePitchTimeThrowHandPitchTypeVelocityHorizontalBreakInducedVerticalBreakKneeStrideFlexionFCKneeStrideFlexionAngVeloPeakShoulderThrowRotationMERElbowThrowFlexionFCHipChestSeparationPeakInjuredDateBodyPartBodySideDiagnosisCombinedDiagnosisGripLeftGripRightGripDateAssessedPerformanceDateAssessedHipExternalRotatationPassiveLeftHipExternalRotatationPassiveRightShoulderExternalRotatationStrengthLeftShoulderExternalRotatationStrengthRightASLRCoreStabilityLeftASLRCoreStabilityRightAvgBrakingForceNewtonsPeakPropulsiveForceNewtonsJumpHeightMetersImpulseRatioLeftAvgBrakingForceNewtonsRightAvgBrakingForceNewtonsJumpDateAssessed
96726KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.0NaNNaNNaNNaNNaNNaN2023-06-06
96727KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.0NaNNaNNaNNaNNaNNaN2023-06-04
96728KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.0NaNNaNNaNNaNNaNNaN2023-06-05
96729KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.01777.0396102723.8696400.6456481.547898939.583941838.4923682023-06-08
96731KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.02032.4689932910.3683920.1449572.6591711151.095628880.9608752023-05-21
96732KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.01755.3116162649.9876320.8874972.1089821006.457676750.4657012023-05-29
96734KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.01884.2910692681.4249750.0051692.4491461053.100362830.0622202023-06-03
96735KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.01916.7819552734.6133081.0267192.2921181088.755632827.9448122023-05-22
96736KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.01937.7166762708.5851291.0476611.2285051070.196536867.1628512023-05-26
96737KYOF1142023-06-1317:30:15RSL85.3905454.118311.61194149.906738434.032176-174.54552196.30086448.1675822023-06-19Arm/ElbowRStrainR Arm/Elbow Strain180.741973193.411142023-06-182023-05-1829.74493423.74919271.1617978.0991051.00.01766.9808062616.4784010.2078351.965835952.444974813.8749042023-06-18